[ use case ]

AI Content Collaboration Agent

Build an AI agent that manages content review workflows over email. It sends drafts to reviewers, collects feedback, tracks revisions, and coordinates approval across teams — without anyone leaving their inbox.

The problem

Content teams juggle reviews across multiple tools — Google Docs comments, Slack threads, Notion pages, and email chains. A blog post might need sign-off from marketing, legal, and engineering, each using different tools and response timelines. Feedback gets scattered. Revisions pile up with no clear status tracking. Deadlines slip because nobody knows who still needs to review.

Email remains the universal lowest common denominator. External reviewers, freelancers, executives, and subject matter experts all check email. But using email for content review manually means endless forwarding, lost context, and a spreadsheet to track who approved what.

The real bottleneck is coordination — sending the right draft version to the right reviewers, parsing their feedback into actionable items, notifying authors, and tracking progress toward publication. This is administrative overhead that does not require human judgment.

How an AI agent solves this

An AI content collaboration agent operates as an automated editor at an address like [email protected]. It manages the entire review cycle through email — distributing drafts, collecting feedback, parsing revision requests, and tracking approvals.

Sends review requests to designated reviewers with draft links and deadlines
Parses free-form feedback into structured, actionable items
Tracks approval status across multiple reviewers per content piece
Sends reminder nudges when review deadlines approach
Notifies authors when feedback arrives, with a summary of changes requested
Detects "LGTM" or approval signals and marks the review as complete

How it works with Robotomail

Robotomail provides the email infrastructure your agent needs. A real mailbox for sending review requests, receiving feedback, and maintaining threaded conversations across the entire revision lifecycle.

1. Provision an editor mailbox

Create mailbox

curl -X POST https://api.robotomail.com/v1/mailboxes \
  -H "Authorization: Bearer rm_live_key" \
  -H "Content-Type: application/json" \
  -d '{
    "address": "editor",
    "domainId": "dom_contentops",
    "displayName": "ContentOps Editor"
  }'

2. Send review requests with context

Your agent sends each reviewer a personalized email with the draft link, revision summary, and a clear deadline.

Send review request

curl -X POST https://api.robotomail.com/v1/mailboxes/{mailbox_id}/messages \
  -H "Authorization: Bearer rm_live_key" \
  -H "Content-Type: application/json" \
  -d '{
    "to": ["[email protected]"],
    "subject": "Review request: Q2 Product Launch Blog Post (Draft 2)",
    "bodyText": "Hi Maria,\n\nDraft 2 of the Q2 product launch blog post is ready for your review. I\'ve incorporated the technical accuracy feedback from Draft 1.\n\nKey changes:\n- Updated performance benchmarks with latest data\n- Added migration guide section per your suggestion\n- Shortened the intro paragraph\n\nPlease reply with your feedback or approve by replying \"LGTM\".\n\nDraft link: https://docs.contentops.co/drafts/q2-launch-v2\n\nDeadline: March 25, 2026\n\nThanks,\nContentOps Editor"
  }'

3. Register a webhook for feedback

curl -X POST https://api.robotomail.com/v1/webhooks \
  -H "Authorization: Bearer rm_live_key" \
  -H "Content-Type: application/json" \
  -d '{
    "url": "https://your-app.com/api/content-inbox",
    "events": ["message.received"],
    "mailboxId": "mbx_editor_01"
  }'

4. Receive reviewer feedback

When a reviewer replies, Robotomail delivers the message to your webhook with full thread context.

Webhook payload

{
  "event": "message.received",
  "data": {
    "id": "msg_c8r2v1",
    "from": "[email protected]",
    "to": ["[email protected]"],
    "subject": "Re: Review request: Q2 Product Launch Blog Post (Draft 2)",
    "text": "The benchmarks section looks great now. Two notes:\n\n1. The migration guide needs a prerequisites section\n2. Can we add a comparison table vs the old version?\n\nOtherwise close to approval.",
    "receivedAt": "2026-03-22T16:45:00Z",
    "threadId": "thr_review_789"
  }
}

5. Agent parses feedback and coordinates revisions

Agent logic

async function handleReviewFeedback(payload) {
  const { from, text, threadId } = payload.data;

  // Find the content piece and reviewer
  const review = await db.reviews.findByThread(threadId);
  const reviewer = await db.reviewers.findByEmail(from);

  // Parse feedback with LLM
  const feedback = await parseFeedback(text);
  // => {
  //   status: "changes_requested",
  //   items: [
  //     { type: "addition", description: "Prerequisites section in migration guide" },
  //     { type: "addition", description: "Comparison table vs old version" }
  //   ],
  //   sentiment: "positive"
  // }

  // Record feedback items
  for (const item of feedback.items) {
    await db.feedbackItems.create({
      reviewId: review.id,
      reviewerId: reviewer.id,
      type: item.type,
      description: item.description,
      status: "pending",
    });
  }

  // Update review status
  await db.reviews.update(review.id, {
    status: feedback.status === "approved" ? "approved" : "revision_needed",
    lastFeedbackAt: new Date(),
  });

  // Acknowledge feedback and notify the author
  const ack = await generateAcknowledgment({
    reviewerName: reviewer.name,
    feedbackItems: feedback.items,
    contentTitle: review.contentTitle,
  });

  await fetch(`https://api.robotomail.com/v1/mailboxes/${mailboxId}/messages`, {
    method: "POST",
    headers: {
      "Authorization": "Bearer rm_live_key",
      "Content-Type": "application/json",
    },
    body: JSON.stringify({
      to: [from],
      subject: `Re: ${review.subject}`,
      bodyText: ack,
      inReplyTo: threadId,
    }),
  });

  // Notify the content author about the feedback
  await fetch(`https://api.robotomail.com/v1/mailboxes/${mailboxId}/messages`, {
    method: "POST",
    headers: {
      "Authorization": "Bearer rm_live_key",
      "Content-Type": "application/json",
    },
    body: JSON.stringify({
      to: [review.authorEmail],
      subject: `Feedback received: ${review.contentTitle}`,
      bodyText: `${reviewer.name} reviewed Draft ${review.draftNumber} and requested changes:\n\n${feedback.items.map(i => `- ${i.description}`).join("\n")}\n\nPlease update the draft and reply when ready for re-review.`,
    }),
  });
}

Key benefits

Inbox-native workflow. Reviewers do not need to learn a new tool or log into a platform. They receive review requests in email and reply with feedback — the way they already work.
Structured from unstructured. The agent parses free-form email feedback into discrete, trackable items. No more digging through threads to find what needs changing.
Multi-reviewer coordination. Track who has reviewed, who is pending, and who approved — across any number of reviewers per content piece.
Automatic follow-ups. Gentle reminder emails go out as deadlines approach. No more manual "just checking in" messages.
Version-aware threads. Robotomail maintains conversation threads across draft versions. Reviewers see the full history of a content piece's evolution in their inbox.

Read the documentation to get started, or learn more about the platform in our launch post. Ready to build? Sign up free.

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